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2. A Digital Study Assistant for Hierarchical Goal Setting Companion Faces the First Real Users
- Author
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International Association for Development of the Information Society (IADIS) and Weber, Felix
- Abstract
Digital Study Assistants (DSA) are an emerging type of software that combines web-based software architectures, various data sources, and algorithms from artificial intelligence (AI) to assist learners in improving their learning-related behaviors. In this paper, we summarize the implementation and results of a field study with a DSA for hierarchical goal-setting (HGS) at the Bremen, Hannover, and Osnabrück universities from November 2021 to April 2022. The results show that 70% of students in the sample chose to get digital assistance for educational goal-setting, which is the highest interest rate among the nine assistance functions available. Of the 290 students who chose to use the assistant, only 10 completed the full assistive intervention, which equals only 3.4%. We conclude that we should improve the usability and user experience and reduce the interaction costs of the intervention.
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- 2022
3. Proceedings of International Conference on Studies in Education and Social Sciences (Antalya, Turkey, October 20-23, 2023). Volume 1
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International Society for Technology, Education and Science (ISTES) Organization, Muhammet Demirbilek, Mahmut Sami Ozturk, Mevlut Unal, Muhammet Demirbilek, Mahmut Sami Ozturk, Mevlut Unal, and International Society for Technology, Education and Science (ISTES) Organization
- Abstract
"Proceedings of International Conference on Studies in Education and Social Sciences" includes full papers presented at the International Conference on Studies in Education and Social Sciences (ICSES) which took place on October 20-23, 2023, in Antalya, Turkey. The aim of the conference is to offer opportunities to share ideas, to discuss theoretical and practical issues and to connect with the leaders in the fields of education and social sciences. The conference is organized annually by the International Society for Technology, Education, and Science (ISTES). The ICSES invites submissions which address the theory, research, or applications in all disciplines of education and social sciences. The ICSES is organized for: faculty members in all disciplines of education and social sciences, graduate students, K-12 administrators, teachers, principals and all interested in education and social sciences. After peer-reviewing process, all full papers are published in the Conference Proceedings. [Individual papers are indexed in ERIC. The month of the conference on the cover page (November) is incorrect. The correct month is October.]
- Published
- 2023
4. Psychological Applications and Trends 2024
- Author
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Clara Pracana, Michael Wang, Clara Pracana, and Michael Wang
- Abstract
This book contains a compilation of papers presented at the International Psychological Applications Conference and Trends (InPACT) 2024, organized by the World Institute for Advanced Research and Science (WIARS), held in International Psychological Applications Conference and Trends (InPACT) 2024, held in Porto, Portugal, from 20 to 22 of April 2024. This conference serves as a platform for scholars, researchers, practitioners, and students to come together and share their latest findings, ideas, and insights in the field of psychology. InPACT 2024 received 526 submissions, from more than 43 different countries all over the world, reviewed by a double-blind process. Submissions were prepared to take the form of Oral Presentations, Posters, Virtual Presentations and Workshops. 189 submissions (overall, 36% acceptance rate) were accepted for presentation at the conference.
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- 2024
5. Is Machine Learning Prediction of Computational Thinking Generalizable across Regions and Cultures?
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Zexuan Pan and Maria Cutumisu
- Abstract
Computational thinking (CT) is a fundamental ability for learners in today's society. Although CT assessments and interventions have been studied widely, little is known about CT predictions. This study predicted students' CT achievement in the ICILS 2018 using five machine learning models. These models were trained on the data from five European countries and then tested on the Korean and the Danish sample, respectively. Results indicate that the models trained on the individualistic-European data were generalizable to the individualistic European country, Denmark, but not to the collectivistic Asian country, Korea. This study fills a void in the CT literature and highlights the importance of considering the contextual relevance of data sources when making algorithmic predictions.
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- 2023
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6. Towards a User Focused Development of a Digital Study Assistant through a Mixed Methods Design
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Schurz, Katharina, Schrumpf, Johannes, Weber, Felix, Lübcke, Maren, Seyfeli, Funda, and Wannemacher, Klaus
- Abstract
Digital Study Assistants (DSA) aim to support individual learning processes by designing them appropriately and efficiently based on recommendations. In this paper we present a prototype of a DSA for students in higher education of three German universities. The digital data driven DSA is integrated into the local learning management system and consists of recommender modules with a certain kind of recommendation for a specific purpose, e.g., recommending Academic Contacts that fit an expressed academic interest. The modules implemented so far use a wide range of methods: Classic rule-based Artificial Intelligence (AI) or Neural Networks, that can detect complex features and patterns in large data sets. To evaluate the current prototype of the DSA we used a mixed methods design approach with concurrently collected user data and qualitative data. A first insight in the user data suggests that recommender modules providing personalized recommendations are more likely to be used by students. A focus group discussion with students confirmed these findings with the suggestion to make the DSA more personal, individual, interactive, supportive, and user-friendly. In conclusion we present ideas for the further development of the prototype based on these findings. [For the full proceedings, see ED621108.]
- Published
- 2021
7. 'You Are Apple, Why Are You Speaking to Me in Turkish?': The Role of English in Voice Assistant Interactions
- Author
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Didem Leblebici
- Abstract
This paper investigates the role of English in voice assistant (Siri, Alexa, Google Assistant) use from the perspective of language ideology. Major commercial companies in the voice assistant market use English as a training language for their speech technologies and offer the most optimised support for standardised varieties of English. This affects the experiences with voice assistants of speakers of non-European languages, i.e., one of the non-target audiences. Drawing on qualitative interview data from Turkish-speaking users who migrated to Germany, the present study reveals that the participants iconize English as the "standard" language in digital contexts, constructing it as the "original" language of speaking computers. By conducting an inductive analysis, the article demonstrates that not only the lack of technological support, but also specific discourses about Artificial Intelligence, impact perceptions of English. These developments have implications for our understandings of prestige and digital literacy in human-machine interactions.
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- 2024
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8. Transnational Higher Education Cultures and Generative AI: A Nominal Group Study for Policy Development in English Medium Instruction
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Peter Bannister, Elena Alcalde Peñalver, and Alexandra Santamaría Urbieta
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Purpose: This purpose of this paper is to report on the development of an evidence-informed framework created to facilitate the formulation of generative artificial intelligence (GenAI) academic integrity policy responses for English medium instruction (EMI) higher education, responding to both the bespoke challenges for the sector and longstanding calls to define and disseminate quality implementation good practice. Design/methodology/approach: A virtual nominal group technique engaged experts (n = 14) in idea generation, refinement and consensus building across asynchronous and synchronous stages. The resulting qualitative and quantitative data were analysed using thematic analysis and descriptive statistics, respectively. Findings: The GenAI Academic Integrity Policy Development Blueprint for EMI Tertiary Education is not a definitive mandate but represents a roadmap of inquiry for reflective deliberation as institutions chart their own courses in this complex terrain. Research limitations/implications: If repeated with varying expert panellists, findings may vary to a certain extent; thus, further research with a wider range of stakeholders may be necessary for additional validation. Practical implications: While grounded within the theoretical underpinnings of the field, the tool holds practical utility for stakeholders to develop bespoke policies and critically re-examine existing frameworks. Social implications: As texts produced by students using English as an additional language are at risk of being wrongly accused of GenAI-assisted plagiarism, owing to the limited efficacy of text classifiers such as Turnitin, the policy recommendations encapsulated in the blueprint aim to reduce potential bias and unfair treatment of students. Originality/value: The novel blueprint represents a step towards bridging concerning gaps in policy responses worldwide and aims to spark discussion and further much-needed scholarly exploration to this end.
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- 2024
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9. Digital Media Educational Processes of Health and Nursing Professionals. Current Developments in Germany
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Seltrecht, Astrid and Josupeit, Franziska
- Abstract
In the age of the industrial revolution 4.0 the question arises as to how far digitization, which is taking place in all areas of life and work, can help meet the challenges of caring for patients or relieve the burden on nursing staff. In the health sector, including professional care, digitization is taking place at a rapid pace. In hospitals, digitization means demand-oriented support by means of information technology or artificial intelligence. Nursing staff in Germany, but also in other countries, are required in occupational everyday life to repeatedly engage in the implementation of new digital technologies and to use these appropriately. So, what is needed is digital competence which leads to responsible and independent handling of digital technologies. Due to the rapid digital progress, this digital competence must enable every working person to react to technical innovations in everyday working life. This requirement of a formal education in view of these digital competences leads to the question, to what extent the curriculums in the training and continuing education of nursing staff are already geared toward digital literacy training. The following article describes the results of a document analysis. The documents are a variety of legal and curricular regulations from the area of training and continuing education in the care sector. [For the full proceedings, see ED625421.]
- Published
- 2021
10. Speculative Futures on ChatGPT and Generative Artificial Intelligence (AI): A Collective Reflection from the Educational Landscape
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Bozkurt, Aras, Xiao, Junhong, Lambert, Sarah, Pazurek, Angelica, Crompton, Helen, Koseoglu, Suzan, Farrow, Robert, Bond, Melissa, Nerantzi, Chrissi, Honeychurch, Sarah, Bali, Maha, Dron, Jon, Mir, Kamran, Stewart, Bonnie, Costello, Eamon, Mason, Jon, Stracke, Christian M., Romero-Hall, Enilda, Koutropoulos, Apostolos, Toquero, Cathy Mae, Singh, Lenandlar, Tlili, Ahm, Lee, Kyungmee, Nichols, Mark, Ossiannilsson, Ebba, Brown, Mark, Irvine, Valerie, Raffaghelli, Juliana Elisa, Santos-Hermosa, Gema, Farrell, Orna, Adam, Taskeen, Thong, Ying Li, Sani-Bozkurt, Sunagul, Sharma, Ramesh C., Hrastinski, Stefan, and Jandric, Petar
- Abstract
While ChatGPT has recently become very popular, AI has a long history and philosophy. This paper intends to explore the promises and pitfalls of the Generative Pre-trained Transformer (GPT) AI and potentially future technologies by adopting a speculative methodology. Speculative future narratives with a specific focus on educational contexts are provided in an attempt to identify emerging themes and discuss their implications for education in the 21st century. Affordances of (using) AI in Education (AIEd) and possible adverse effects are identified and discussed which emerge from the narratives. It is argued that now is the best of times to define human vs AI contribution to education because AI can accomplish more and more educational activities that used to be the prerogative of human educators. Therefore, it is imperative to rethink the respective roles of technology and human educators in education with a future-oriented mindset.
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- 2023
11. Concept Maps for Formative Assessment: Creation and Implementation of an Automatic and Intelligent Evaluation Method
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Tom Bleckmann and Gunnar Friege
- Abstract
Formative assessment is about providing and using feedback and diagnostic information. On this basis, further learning or further teaching should be adaptive and, in the best case, optimized. However, this aspect is difficult to implement in reality, as teachers work with a large number of students and the whole process of formative assessment, especially the evaluation of student performance takes a lot of time. To address this problem, this paper presents an approach in which student performance is collected through a concept map and quickly evaluated using Machine Learning techniques. For this purpose, a concept map on the topic of mechanics was developed and used in 14 physics classes in Germany. After the student maps were analysed by two human raters on the basis of a four-level feedback scheme, a supervised Machine Learning algorithm was trained on the data. The results show a very good agreement between the human and Machine Learning evaluation. Based on these results, an embedding in everyday school life is conceivable, especially as support for teachers. In this way, the teacher can use and interpret the automatic evaluation and use it in the classroom.
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- 2023
12. Mapping the Evolution Path of Citizen Science in Education: A Bibliometric Analysis
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Yenchun Wu and Marco Fabio Benaglia
- Abstract
For over two decades now, the application of Citizen Science to Education has been evolving, and fundamental topics, such as the drivers of motivation to participate in Citizen Science projects, are still under discussion. Some recent developments, though, like the use of Artificial Intelligence to support data collection and validation, seem to point to a clear-cut divergence from the mainstream research path. The objective of this paper is to summarise the development trajectory of research on Citizen Science in Education so far, and then shed light on its future development, to help researchers direct their efforts towards the most promising open questions in this field. We achieved these objectives by using the lens of the Affordance-Actualisation theory and the Main Path Analysis method.
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- 2024
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13. The Role of Universities in Modern Society
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Moscardini, A. O., Strachan, R., and Vlasova, T.
- Abstract
This is a conceptual paper that examines the origin and development of universities and their current role in global society. There has been an unprecedented and exponential growth of technology and artificial intelligence capabilities over the past ten years which is challenging current working practices and affecting all areas of society. The paper examines how this role may change to match the new demands placed on them by a digitally enabled society that has greater leisure time. The design of the paper is first to detail some of the changes in work practices that are taking place and how these will impact on society. It then offers several ways in which universities could modify their role to respond to these emerging challenges. This could include new courses, new organisational structures and new pedagogical practices. The paper provides a platform for discussion and debate around the strategic vision and direction of travel for higher education.
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- 2022
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14. When Probabilities Are Not Enough--A Framework for Causal Explanations of Student Success Models
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Cohausz, Lea
- Abstract
Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models outputting simple probabilities are not enough to achieve these ambitious goals. In this paper, we argue that they can be a first exploratory step of a pipeline aiming to be capable of reaching the mentioned goals. By using Explainable Artificial Intelligence (XAI) methods, such as SHAP and LIME, we can understand what features matter for the model and make the assumption that features important for successful models are also important in real life. By then additionally connecting this with an analysis of counterfactuals and a theory-driven causal analysis, we can begin to reasonably understand not just "if" a student will struggle but "why" and provide fitting help. We evaluate the pipeline on an artificial dataset to show that it can, indeed, recover complex causal mechanisms and on a real-life dataset showing the method's applicability. We further argue that collaborations with social scientists are mutually beneficial in this area but also discuss the potential negative effects of personal intervention systems and call for careful designs.
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- 2022
15. Proceedings of the International Conference on Educational Data Mining (EDM) (11th, Raleigh, North Carolina, July 16-20, 2018)
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International Educational Data Mining Society, Boyer, Kristy Elizabeth, and Yudelson, Michael
- Abstract
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37 accepted as short papers. This year's conference features three invited talks: Tiffany Barnes, Professor at North Carolina State University in Raleigh, North Carolina; Jodi Forlizzi, Geschke Director of the HCI Institute and Professor at Carnegie Mellon University; and Jim Larimore, Chief Officer of Center for Equity in Learning at ACT, Inc. Together with the "Journal of Educational Data Mining" ("JEDM"), the EDM 2018 conference supports a "JEDM" Track that provides researchers a venue to deliver more substantial mature work than is possible in a conference proceeding and to present their work to a live audience. Three such papers are featured this year. The papers submitted to this track followed the "JEDM" peer review process. The main conference invited contributions to an Industry Track in addition to the main track. The EDM 2018 Industry Track received ten submissions of which six were accepted, a tangible improvement over last year, with only four submissions total, all of which were accepted. This expansion of the industry track represents an intentional goal to better connect industry researchers with the academic research community. The EDM conference continues its tradition of providing opportunities for young researchers to present their work and receive feedback from their peers and senior researchers. The doctoral consortium this year features 14 such presentations, more than double compared to the prior year. In addition to the main program, there are four workshops: (1) Educational Data Mining in Computer Science Education (CSEDM); (2) Proposal Policy & EDM: Norms, Risks, and Safeguards; (3) replicate.education: A Workshop on Large Scale Education Replication; and (4) Scientific Findings from the ASSISTments Longitudinal Data.
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- 2018
16. EdMedia 2018: World Conference on Educational Media and Technology (Amsterdam, The Netherlands, June 25-29, 2018)
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Association for the Advancement of Computing in Education and Bastiaens, Theo
- Abstract
The Association for the Advancement of Computing in Education (AACE) is an international, non-profit educational organization. The Association's purpose is to advance the knowledge, theory, and quality of teaching and learning at all levels with information technology. "EdMedia + Innovate Learning: World Conference on Educational Media and Technology" took place in Amsterdam, The Netherlands, June 25-29, 2018. These proceedings contain 308 papers, including 14 award papers. The award papers cover topics such as Open Education Resources (OER) certification for higher education; a cooperative approach to the challenges of implementing e-assessments; developing an e-learning system for English conversation practice using speech recognition and artificial intelligence; the Learning Experience Technology Usability Design Framework; developing strategies for digital transformation in higher education; pre-service teachers' readiness to use Information and Communication Technology (ICT) in education; teacher development through technology in a short-term study abroad program; Austria's higher education e-learning landscape; a digitised educational application focused on the water cycle in nature carried out in a secondary school in Ireland; evaluative research on virtual and augmented reality for children; how children use computational thinking skills when they solve a problem using the Ozobot; a strategy to connect curricula with the digital world; the learning portfolio in higher education; and adult playfulness in simulation-based healthcare education. [For the 2017 proceedings, see ED605571.]
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- 2018
17. AI-readiness and production resilience: empirical evidence from German manufacturing in times of the Covid-19 pandemic.
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Lerch, Christian M., Heimberger, Heidi, Jäger, Angela, Horvat, Djerdj, and Schultmann, Frank
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COVID-19 pandemic ,ARTIFICIAL intelligence ,MANUFACTURING industries ,STAY-at-home orders - Abstract
The outbreak of the Covid-19 pandemic led to restrictions in production worldwide. Numerous firms were affected and unable to keep up production due to lockdowns. In disruptive events like this, the resilience of the production system is of central importance, as the survivability of the entire firm depends on it. In this context, the literature argues that cutting-edge technologies, such as Artificial Intelligence (AI), raise the proactive and reactive capabilities of firms, enabling them to better resist and recover from disruptive events and thus, show a higher resilience. This paper takes up this topic and observes the Covid-19 pandemic with the aim to analyse whether a firm's AI-readiness had an impact on its production resilience during the spring 2020 lockdown in Germany. For this purpose, we combine two large-scale surveys containing data from 237 manufacturers in Germany and test hypotheses based on quantitative analyses. Our results show that firms could indeed benefit from AI-enabled production during the lockdown. However, it is also clear that manufacturers have to exceed a certain AI threshold to significantly increase their resilient capabilities and realise positive effects. Our findings not only hold implications for research, but also provide recommendations for the resilience management of manufacturers. [ABSTRACT FROM AUTHOR]
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- 2024
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18. Research on Data Processing Security System Based on Bio commercial technology and Artificial Intelligence.
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Tang Li, Zhao Zhiyu, Li Biaoqi, and Xu Min
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INFORMATION storage & retrieval systems ,ARTIFICIAL intelligence ,HUMAN fingerprints ,MEDICAL equipment ,DATA security ,ELECTRONIC data processing ,DIGITAL technology - Abstract
Data security has become an increasingly important concern for organizations and individuals in the digital age. To address this issue, there has been growing interest in using bio-commercial technology and artificial intelligence (AI) to develop innovative security solutions. This paper presents a research study on the development of a data processing secure new entrants in the market for medical devices in Germany can use the use of biometric data, such as fingerprints, iris scans, and voice recognition, in combination with AI algorithms to enhance the security of data processing. The paper provides an overview of the technical framework and architecture of the proposed system, and evaluates its effectiveness in comparison to traditional security measures. The study uses a combination of quantitative and qualitative research methods, including surveys, interviews, and simulations, to collect and analyze data on the performance, accuracy, and usability of the proposed system. The results suggest that the data processing security system based on bio-commercial technology and AI is highly effective in preventing unauthorized access and enhancing data protection. The system provides a high level of accuracy, speed, and user-friendliness, making it a viable alternative to traditional security measures. The paper concludes with a discussion of the implications of the study for the field of data security and future research directions. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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19. Digitalisierung und digitale Teilhabe von Menschen mit Behinderung.
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Rausch-Berhie, Friederike and Busch, Dörte
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CONVENTION on the Rights of Persons with Disabilities ,SOCIAL participation ,ASSISTIVE technology ,ARTIFICIAL intelligence ,PEOPLE with disabilities ,SUPPORT groups - Abstract
Copyright of Sozialer Fortschritt is the property of Duncker & Humblot GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2022
- Full Text
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20. Subnational AI policy: shaping AI in a multi-level governance system.
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Liebig, Laura, Güttel, Licinia, Jobin, Anna, and Katzenbach, Christian
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NETWORK governance ,ARTIFICIAL intelligence ,KNOWLEDGE transfer ,ECONOMIC policy ,ECONOMIC research ,GOVERNMENT policy - Abstract
The promises and risks of Artificial Intelligence permeate current policy statements and have attracted much attention by AI governance research. However, most analyses focus exclusively on AI policy on the national and international level, overlooking existing federal governance structures. This is surprising because AI is connected to many policy areas, where the competences are already distributed between the national and subnational level, such as research or economic policy. Addressing this gap, this paper argues that more attention should be dedicated to subnational efforts to shape AI and asks which themes are discussed in subnational AI policy documents with a case study of Germany's 16 states. Our qualitative analysis of 34 AI policy documents issued on the subnational level demonstrates that subnational efforts focus on knowledge transfer between research and industry actors, the commercialization of AI, different economic identities of the German states, and the incorporation of ethical principles. Because federal states play an active role in AI policy, analysing AI as a policy issue on different levels of government is necessary and will contribute to a better understanding of the developments and implementations of AI strategies in different national contexts. [ABSTRACT FROM AUTHOR]
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- 2024
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21. Memristive computing in Germany.
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Fey, Dietmar
- Subjects
SUCCESSIVE approximation analog-to-digital converters ,ARTIFICIAL intelligence ,PHASE change memory - Abstract
Such behaviour is to observe in non-volatile memory (NVM) elements, e.g., in resistive RAMs (ReRAMs), spin-torque transfer (STT)-MRAMs, phase change memory (PCM)-RAMs or polarization-based ferroelectric RAMs (FeRAM). It was in 1971 when Leon Chua concluded by a plausibility consideration based on symmetry that there should exist a fourth fundamental element in electronics in addition to resistance, capacitance and inductance. These properties include, e.g., a pinched hysteresis curve of the current/voltage waveform, i.e., the curve passes through the point of origin in contrast to a usual hysteresis curve (according to a paper title from Leon Chua "if it's pinched, it's a memristor"). [Extracted from the article]
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- 2023
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22. GENERAL ASSUMPTIONS FOR PROJECT MANAGEMENT IN INDUSTRY 4.0.
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GAJDZIK, Bożena and KOPEĆ, Grzegorz
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INDUSTRY 4.0 ,PROJECT management ,ARTIFICIAL intelligence ,MANUFACTURING processes ,INDUSTRIAL efficiency - Abstract
Purpose: Authors of the paper develop the main assumptions for project management in the Industry 4.0, and present them in the short form as basic knowledge, useful for managing smart manufacturing (SM) projects in companies. Design/methodology/approach: the process of preparing SM (smart manufacturing) projects and their implementation, in the Fourth Industrial Revolution, have been changed, due to the importance of the issue of linking more and more intelligent machines, IT-computer programs and monitored processes into integrated technological systems of key importance for the construction of cyber-physical production systems (CPS). The paper applies a conceptual analysis of possible areas of change in project management (PM) when enterprises build the smart manufacturing (SM). Findings/conclusions: companies building the smart environment must adapt their organization of project management to the new requirements and opportunities of Industry 4.0 (I 4.0) technologies. Research limitations: the narrow scope of knowledge about the ongoing changesin SM project management is due to the short period of experience (the Industry 4.0 concept has been implemented since 2011), therefore the authors have only presented the framework of changes in organization of project management. Practical implications: the authors' intention was to initiate a practical discussion about the changes in project management in the ongoing industrial revolution. Originality/value: Since 2011, when the government of the Federal Republic of Germany recognized the concept of "Industrie 4.0" as the key strategy of innovative development, Industry 4.0 has become an important discussed topic among practitioners and researchers. The fourth industrial revolution is expected to result in a leap in the efficiency of companies operating in the intelligent technological environment. Key technologies or pillars of Industry 4.0 are implemented in manufacturing enterprises to build the smart manufacturing processes. Enterprises develop new projects and make investments in order to create Cyber-Physical Production Systems (CPPS). [ABSTRACT FROM AUTHOR]
- Published
- 2022
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23. Current landscape of hospital information systems in gynecology and obstetrics in Germany: a survey of the commission Digital Medicine of the German Society for Gynecology and Obstetrics.
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Pfob, André, Griewing, Sebastian, Seitz, Katharina, Hillen, Christoph, Becker, Sven, Bayer, Christian, Wagner, Uwe, Fasching, Peter, Wallwiener, Markus, For the Kommission Digitale Medizin, Deutsche Gesellschaft für Gynäkologie und Gebursthilfe (DGGG), Abele, Harald, Alexa, Matthias, Cieslik, Jan Philipp, Dannehl, Dominik, Deutsch, Thomas, Fehm, Tanja, Graupner, Oliver, Hackelöer, Max, Hartkopf, Andreas, and Hein, Alexander
- Subjects
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HOSPITALS , *INFORMATION storage & retrieval systems , *MEDICAL personnel , *GYNECOLOGY , *OBSTETRICS - Abstract
Purpose: Hospital information systems (HIS) play a critical role in modern healthcare by facilitating the management and delivery of patient care services. We aimed to evaluate the current landscape of HIS in the specialty of gynecology and obstetrics in Germany. Methods: An anonymous questionnaire was distributed via the German Society of Gynecology and Obstetrics newsletter in December 2022. The questionnaire covered the domains baseline demographic information, satisfaction with daily use, satisfaction with implementation, and degree of digitization. Results: Ninety-one participants completed the survey. Median age was 34 years; 67.4% (60 of 89) were female, and 32.6% (29 of 89) were male. Of the survey participants, 47.7% (42 of 88) were residents, 26.1% (23 of 91) senior physicians, and 9.1% (8 of 88) medical directors. The degree of digitization of clinical documentation is mainly mixed digital and paper-based (64.0%, 57 of 89) while 16.9% (15 of 89) operate mainly paper-based. The current HIS has been in use on average for 9 years. The median number of different software systems used in daily routine is 4. About 33.7% (30 of 89) would likely or very likely recommend their current HIS to a colleague. Conclusions: The current landscape of HIS in gynecology and obstetrics in Germany is characterized by a high heterogeneity of systems with low interoperability and long service life; thus, many healthcare professionals are not satisfied. There is both a need to enhance and an interest in modernizing the technological infrastructure to meet today's requirements for patient care. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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24. Technologischer Wandel trifft Politikfeldwandel: KI-Politik als Ausdifferenzierung von Digitalpolitik.
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Goldmann, Anne
- Subjects
TECHNOLOGICAL innovations ,ARTIFICIAL intelligence ,POLICY analysis ,CONTENT analysis ,COMMUNICATION methodology ,MACHINE theory ,AMBIVALENCE ,COMPUTER literacy - Abstract
Copyright of Der Moderne Staat is the property of Verlag Barbara Budrich GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2022
- Full Text
- View/download PDF
25. Expectations and attitudes towards medical artificial intelligence: A qualitative study in the field of stroke.
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Amann, Julia, Vayena, Effy, Ormond, Kelly E., Frey, Dietmar, Madai, Vince I., and Blasimme, Alessandro
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CLINICAL decision support systems ,MACHINE learning ,ARTIFICIAL intelligence ,ATTITUDES toward technology ,MEDICAL personnel ,NETWORK governance - Abstract
Introduction: Artificial intelligence (AI) has the potential to transform clinical decision-making as we know it. Powered by sophisticated machine learning algorithms, clinical decision support systems (CDSS) can generate unprecedented amounts of predictive information about individuals' health. Yet, despite the potential of these systems to promote proactive decision-making and improve health outcomes, their utility and impact remain poorly understood due to their still rare application in clinical practice. Taking the example of AI-powered CDSS in stroke medicine as a case in point, this paper provides a nuanced account of stroke survivors', family members', and healthcare professionals' expectations and attitudes towards medical AI. Methods: We followed a qualitative research design informed by the sociology of expectations, which recognizes the generative role of individuals' expectations in shaping scientific and technological change. Semi-structured interviews were conducted with stroke survivors, family members, and healthcare professionals specialized in stroke based in Germany and Switzerland. Data was analyzed using a combination of inductive and deductive thematic analysis. Results: Based on the participants' deliberations, we identified four presumed roles that medical AI could play in stroke medicine, including an administrative, assistive, advisory, and autonomous role AI. While most participants held positive attitudes towards medical AI and its potential to increase accuracy, speed, and efficiency in medical decision making, they also cautioned that it is not a stand-alone solution and may even lead to new problems. Participants particularly emphasized the importance of relational aspects and raised questions regarding the impact of AI on roles and responsibilities and patients' rights to information and decision-making. These findings shed light on the potential impact of medical AI on professional identities, role perceptions, and the doctor-patient relationship. Conclusion: Our findings highlight the need for a more differentiated approach to identifying and tackling pertinent ethical and legal issues in the context of medical AI. We advocate for stakeholder and public involvement in the development of AI and AI governance to ensure that medical AI offers solutions to the most pressing challenges patients and clinicians face in clinical care. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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26. A Bibliometric Analysis of the Field of Artificial Intelligence in Cariology.
- Author
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GÜLŞEN, İbrahim Tevfik, ERDEM, Ruşen, GENÇ, Yavuz Selim, and YALINIZ, Gülbeddin
- Subjects
ARTIFICIAL intelligence ,BIBLIOMETRICS ,DENTAL caries ,SCIENCE databases ,WEB databases - Abstract
Copyright of Selcuk Dental Journal is the property of Selcuk Dental Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2024
- Full Text
- View/download PDF
27. Legal conform data sets for yard tractors and robots: AI-based law compliance check on the right to one's image.
- Author
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Kruse, Niklas and Schöning, Julius
- Subjects
- *
ARTIFICIAL intelligence , *ARTIFICIAL neural networks , *LEGAL compliance , *DATA protection laws , *AGRICULTURE - Abstract
The growing integration of AI in agriculture necessitates access to diverse data sets for training artificial intelligence (AI) systems. Manufacturers often face challenges due to a perceived shortage of valid data sets, highlighting the need for centralized platforms offering high-quality data. While global AI regulations are yet to be established, existing laws govern data collection, creation, labeling, and processing for AI training in various legal systems. The absence of explicit AI laws prompts a call for platforms supplying data to adhere to relevant regulations, especially in areas where AI controls devices interacting with humans, such as collision warning systems in yard tractors and robots. Compliance is crucial, given the complexity of rules governing data sets featuring people, animals, and buildings. The paper focuses on how to check the compliant data sets in Germany's legal context, focusing on situations in farm yards. People are often visible on such data sets; thus, the data set must preserve the right to informational self-determination and one's image, which is prevalent in many legal systems. Images portraying people typically qualify as personal data, requiring careful anonymization to address privacy concerns. The paper uses artificial neural networks (ANN) to remove images that contradict people's rights on one's image; thus, data sets that comply with data protection laws can be created. It also addresses the lesser-explored issue of the right to one's image in German law. Though AI training may not be impeded, dissemination via digital platforms must adhere to legal boundaries, even if metadata is absent. The paper suggests an AI solution to identify images within legal limits, detect violations, and modify them to create a legally compliant data set respecting the right to one's image. • Discussing legal conform data sets for the agricultural application domain. • Providing a data set of 2694 images covering the categories: – class (I) not legally compliant and – class (II) legally compliant on the right to one's image; cf. Fig. 1. • Identifying the gap in ANN data sets and models for law compliance checks. • Train and benchmark ANN models for checking law compliance – on the right to one's image; – cf. Tab. 1, Tab. 2, and Fig. 3. • Promoting the importance of AI-based law compliance checks for – detecting violations against the law and – developing compliant AI systems in agriculture. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
28. 72. Plenarsitzung der CES.
- Subjects
ARTIFICIAL intelligence ,STATISTICIANS ,SEMINARS ,STATISTICS ,EMPLOYMENT - Abstract
Copyright of WISTA Wirtschaft und Statistik is the property of Statistisches Bundesamt and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2024
29. Technologieversprechen Künstliche Intelligenz. Vergangene und gegenwärtige Konjunkturen in der Bundesrepublik.
- Author
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Hirsch-Kreinsen, Hartmut and Krokowski, Thorben
- Subjects
INFORMATION technology ,ARTIFICIAL intelligence ,EVERYDAY life ,COMPUTER software ,WINTER - Abstract
Copyright of Berliner Journal für Soziologie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2023
- Full Text
- View/download PDF
30. A comparative analysis of the application of Fourth Industrial Revolution technologies in the energy sector: A case study of South Africa, Germany and China.
- Author
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Bhagwan, N. and Evans, M.
- Subjects
INDUSTRY 4.0 ,ENERGY industries ,CRONBACH'S alpha ,ARTIFICIAL intelligence ,TECHNOLOGY transfer ,INDUSTRIAL applications - Abstract
Fourth Industrial Revolution (4IR) technologies have elevated the capabilities and possibilities of improvement and efficiency in the energy sector. This paper interrogates how energy companies in South Africa, Germany and China apply 4IR technologies. A total of 26 energy companies in those countries were surveyed. An analysis was carried out using the Cronbach Alpha, Kruskal-Wallis and Mann-Whitney tests. Survey results indicate that 85% of companies acknowledge good levels of participation in the 4IR, and were clear about which 4IR technologies are important, although few companies develop these themselves. Technologies enabling access to big, real-time data (BRTD) and BRTD analysis software, are valued the most in measured importance, efficiency, reliability and ability to be integrated across the energy system. The transfer of data using the Internet of things ranked highly as a 4IR technology, whereas artificial intelligence, robotics and machine-human integration (also referred to as machine-human interaction) are considered less important, efficient, and reliable. China rates 4IR technologies as more important than South Africa and Germany do. For South Africa to be competitive in the global energy sector it needs to engage with and embrace 4IR technologies to a greater extent. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
31. The 27th International Conference on Case-Based Reasoning.
- Author
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Althoff, Klaus-Dieter, Bach, Kerstin, Bergmann, Ralph, and Marling, Cindy
- Subjects
CASE-based reasoning ,CONFERENCES & conventions ,ARTIFICIAL intelligence - Abstract
The 27th International Conference on Case-Based Reasoning was held September 8--12, 2019, in Otzenhausen, Germany. The theme of the conference was explainable artificial intelligence. The conference featured four invited talks, an invited panel, four workshops, a doctoral consortium, four technical paper sessions, and a poster and system demo session. This report summarizes conference highlights. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
32. Adoption of Artificial Intelligence Technologies in German SMEs - Results from an Empirical Study.
- Author
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Ulrich, Patrick, Frank, Vanessa, and Kratt, Mona
- Subjects
ARTIFICIAL intelligence ,SMALL business ,ECONOMIC activity ,BUSINESS enterprises - Abstract
Artificial intelligence (AI) is globally regarded as one of the most important technologies of the future. Germany is not considered a pioneer in the field of AI in the international context, and the implementation of AI technologies is rather sluggish. As the German economy is mainly driven by SMEs, the implementation of AI in SMEs is a main success factor. This paper discusses the implementation perspectives of AI in German SMEs based on an empirical study from the year 2020 among 283 companies. [ABSTRACT FROM AUTHOR]
- Published
- 2021
33. The impact of corporate identity on corporate social responsibility disclosure.
- Author
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Michaels, Anne and Grüning, Michael
- Subjects
SOCIAL responsibility of business ,CORPORATE image ,CONTENT analysis ,ARTIFICIAL intelligence ,CORPORATIONS - Abstract
Corporate social responsibility (CSR) is of increasing importance for the long-term success of corporations. Extending existing literature this paper explores corporate identity as important determinant for CSR disclosure. The relationship was examined based on 498 German companies that provided English language CSR reports and responded to a company survey measuring CSR-oriented corporate identity. CSR disclosure has been analyzed with an automated content analysis technique using artificial intelligence. Results indicate that value chain and future-oriented dimensions, which were more pronounced in mature CSR concepts, foster CSR disclosure, while introversive corporate identity dimensions that were strong in low level CSR concepts hinder the release of CSR information. The paper shows that a tradition of social responsibility and values results into a low perceived need for legitimacy and outwards communication. The findings support the view that that a combination of voluntary disclosure theory and legitimacy theory is necessary to explain the drivers and constraints of CSR disclosure. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
34. Application of Artificial Intelligence In Small and Medium-Sized Enterprises.
- Author
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Szedlak, Christoph, Poetters, Patrick, and Leyendecker, Bert
- Subjects
ARTIFICIAL intelligence ,SMALL business ,INTERNATIONAL business enterprises ,DIGITIZATION - Abstract
Massive improvements in deep learning methods have led to several new industrial artificial intelligence (AI) applications that made AI relevant for every company that aims to keep competitive. Thus, AI is no longer a matter for the global Tech Companies only, but also concerns any small and medium-sized enterprise (SME). This paper examines the degree of dispersion of AI in SMEs in north-western Germany and reveals barriers and concerns when it comes to the deployment of industrial AI applications. Therefore, selected SMEs were surveyed in a standardised online survey. Currently, AI is rarely used by SMEs in north-western Germany. Few SMEs are concerned with developing their own applications, because this process is very expensive, lengthy and often comes with a high risk of failure. Rather, SMEs increasingly rely on AI-as-a-service and prefer to use cloud-based solutions. There are various reasons that make companies hesitate. Perceived barriers depend on the current implementation status of SMEs, also indicating data-related misconceptions and a lack of know-how. [ABSTRACT FROM AUTHOR]
- Published
- 2020
35. Accelerating Energy-Economic Simulation Models via Machine Learning-Based Emulation and Time Series Aggregation.
- Author
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Bogensperger, Alexander J., Fabel, Yann, and Ferstl, Joachim
- Subjects
TIME series analysis ,CLUSTER sampling ,ADAPTIVE sampling (Statistics) ,SUPERVISED learning ,SIMULATION methods & models ,STATISTICAL sampling ,K-means clustering ,CITIES & towns - Abstract
Energy-economic simulation models with high levels of detail, high time resolutions, or large populations (e.g., distribution networks, households, electric vehicles, energy communities) are often limited due to their computational complexity. This paper introduces a novel methodology, combining cluster-based time series aggregation and sampling methods, to efficiently emulate simulation models using machine learning and significantly reduce both simulation and training time. Machine learning-based emulation models require sufficient and high-quality data to generalize the dataset. Since simulations are computationally complex, their maximum number is limited. Sampling methods come into play when selecting the best parameters for a limited number of simulations ex ante. This paper introduces and compares multiple sampling methods on three energy-economic datasets and shows their advantage over a simple random sampling for small sample-sizes. The results show that a k-means cluster sampling approach (based on unsupervised learning) and adaptive sampling (based on supervised learning) achieve the best results especially for small sample sizes. While a k-means cluster sampling is simple to implement, it is challenging to increase the sample sizes if the emulation model does not achieve sufficient accuracy. The iterative adaptive sampling is more complex during implementation, but can be re-applied until a certain accuracy threshold is met. Emulation is then applied on a case study, emulating an energy-economic simulation framework for peer-to-peer pricing models in Germany. The evaluated pricing models are the "supply and demand ratio" (SDR) and "mid-market rate pricing" (MMR). A time series aggregation can reduce time series data of municipalities by 99.4% with less than 5% error for 98.2% (load) and 95.5% (generation) of all municipalities and hence decrease the simulation time needed to create sufficient training data. This paper combines time series aggregation and emulation in a novel approach and shows significant acceleration by up to 88.9% of the model's initial runtime for the simulation of the entire population of around 12,000 municipalities. The time for re-calculating the population (e.g., for different scenarios or sensitivity analysis) can be increased by a factor of 1100 while still retaining high accuracy. The analysis of the simulation time shows that time series aggregation and emulation, considered individually, only bring minor improvements in the runtime but can, however, be combined effectively. This can significantly speed up both the simulation itself and the training of the emulation model and allows for flexible use, depending on the capabilities of the models and the practitioners. The results of the peer-to-peer pricing for approximately 12,000 German municipalities show great potential for energy communities. The mechanisms offer good incentives for the addition of necessary flexibility. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
36. How much do we see? On the explainability of partial dependence plots for credit risk scoring.
- Author
-
Szepannek, Gero and Lübke, Karsten
- Subjects
CREDIT scoring systems ,MACHINE learning ,ARTIFICIAL intelligence ,CREDIT analysis - Abstract
Risk prediction models in credit scoring have to fulfil regulatory requirements, one of which consists in the interpretability of the model. Unfortunately, many popular modern machine learning algorithms result in models that do not satisfy this business need, whereas the research activities in the field of explainable machine learning have strongly increased in recent years. Partial dependence plots denote one of the most popular methods for model-agnostic interpretation of a feature's effect on the model outcome, but in practice they are usually applied without answering the question of how much can actually be seen in such plots. For this purpose, in this paper a methodology is presented in order to analyse to what extent arbitrary machine learning models are explainable by partial dependence plots. The proposed framework provides both a visualisation, as well as a measure to quantify the explainability of a model on an understandable scale. A corrected version of the German credit data, one of the most popular data sets of this application domain, is used to demonstrate the proposed methodology. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
37. TOWARDS INTELLIGENT GEO-DATABASE SUPPORT FOR EARTH SYSTEM OBSERVATION: IMPROVING THE PREPARATION AND ANALYSIS OF BIG SPATIO-TEMPORAL RASTER DATA.
- Author
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Mazroob Semnani, N., Breunig, M., Al-Doori, M., Heck, A., Kuper, P., and Kutterer, H.
- Subjects
SYNTHETIC aperture radar ,REMOTE sensing ,TEMPORAL databases ,DEFORMATION of surfaces ,SURFACE of the earth ,TELECOMMUNICATION satellites ,ARTIFICIAL intelligence - Abstract
The European COPERNICUS program provides an unprecedented breakthrough in the broad use and application of satellite remote sensing data. Maintained on a sustainable basis, the COPERNICUS system is operated on a free-and-open data policy. Its guaranteed availability in the long term attracts a broader community to remote sensing applications. In general, the increasing amount of satellite remote sensing data opens the door to the diverse and advanced analysis of this data for earth system science.However, the preparation of the data for dedicated processing is still inefficient as it requires time-consuming operator interaction based on advanced technical skills. Thus, the involved scientists have to spend significant parts of the available project budget rather on data preparation than on science. In addition, the analysis of the rich content of the remote sensing data requires new concepts for better extraction of promising structures and signals as an effective basis for further analysis.In this paper we propose approaches to improve the preparation of satellite remote sensing data by a geo-database. Thus the time needed and the errors possibly introduced by human interaction are minimized. In addition, it is recommended to improve data quality and the analysis of the data by incorporating Artificial Intelligence methods. A use case for data preparation and analysis is presented for earth surface deformation analysis in the Upper Rhine Valley, Germany, based on Persistent Scatterer Interferometric Synthetic Aperture Radar data. Finally, we give an outlook on our future research. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
38. Application of the Deep CNN-Based Method in Industrial System for Wire Marking Identification.
- Author
-
Szajna, Andrzej, Kostrzewski, Mariusz, Ciebiera, Krzysztof, Stryjski, Roman, and Woźniak, Waldemar
- Subjects
ARTIFICIAL intelligence ,MANUFACTURING processes ,PRODUCTION control ,CONVOLUTIONAL neural networks ,COMPUTER science - Abstract
Industry 4.0, a term invented by Wolfgang Wahlster in Germany, is celebrating its 10th anniversary in 2021. Still, the digitalization of the production environment is one of the hottest topics in the computer science departments at universities and companies. Optimization of production processes or redefinition of the production concepts is meaningful in light of the current industrial and research agendas. Both the mentioned optimization and redefinition are considered in numerous subtopics and technologies. One of the most significant topics in these areas is the newest findings and applications of artificial intelligence (AI)—machine learning (ML) and deep convolutional neural networks (DCNNs). The authors invented a method and device that supports the wiring assembly in the control cabinet production process, namely, the Wire Label Reader (WLR) industrial system. The implementation of this device was a big technical challenge. It required very advanced IT technologies, ML, image recognition, and DCNN as well. This paper focuses on an in-depth description of the underlying methodology of this device, its construction, and foremostly, the assembly industrial processes, through which this device is implemented. It was significant for the authors to validate the usability of the device within mentioned production processes and to express both advantages and challenges connected to such assembly process development. The authors noted that in-depth studies connected to the effects of AI applications in the presented area are sparse. Further, the idea of the WLR device is presented while also including results of DCNN training (with recognition results of 99.7% although challenging conditions), the device implementation in the wire assembly production process, and its users' opinions. The authors have analyzed how the WLR affects assembly process time and energy consumption, and accordingly, the advantages and challenges of the device. Among the most impressive results of the WLR implementation in the assembly process one can be mentioned—the device ensures significant process time reduction regardless of the number of characters printed on a wire. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
39. RANKING OF CURRENT INFORMATION TECHNOLOGIES BY RISK AND REGULATORY COMPLIANCE OFFICERS AT FINANCIAL INSTITUTIONS -- A GERMAN PERSPECTIVE.
- Author
-
Becker, Michael and Buchkremer, Rüdiger
- Subjects
INFORMATION technology ,REGULATORY compliance ,FINANCIAL institutions ,ETHICS & compliance officers ,ARTIFICIAL intelligence - Abstract
This paper provides new insights on the relevance of new information technologies for the risk and regulatory compliance management of financial institutions in Germany. For this purpose, 62 executive risk managers and compliance officers have been surveyed with respect to risk categories, regulatory requirements as well as new technologies with an emphasis on artificial intelligence. The results of this survey are compared to the scientific literature and to four existing studies of 2016 and 2017, respectively. This research shows that artificial intelligence, big data and cybersecurity technologies are on top of the agenda of financial institutions in Germany. Moreover, the majority of participants are convinced that artificial intelligence solutions will widely be implemented and used in the risk and regulatory compliance environment by the end of 2022. [ABSTRACT FROM AUTHOR]
- Published
- 2018
40. Universal Basic Income Universally Welcomed? – Relevance of Socio-Demographic and Psychological Variables for Acceptance in Germany.
- Author
-
Sureth, Antonia, Gierke, Lioba, Nachtwei, Jens, Ziegler, Matthias, Decker, Oliver, Zenger, Markus, and Brähler, Elmar
- Subjects
BASIC income ,ACCEPTANCE (Psychology) ,STANDARD of living ,ARTIFICIAL intelligence ,TECHNOLOGICAL unemployment - Abstract
The COVID-19 pandemic plunged economies into recessions and advancements in artificial intelligence create widespread automation of job tasks. A debate around how to address these challenges has moved the introduction of a universal basic income (UBI) center stage. However, existing UBI research mainly focuses on economic aspects and normative arguments but lacks an individual perspective that goes beyond examining the association between socio-demographic characteristics and UBI support. We add to this literature by investigating not only socio-demographic but also psychological predictors of UBI acceptance in a multivariate analysis using a representative sample of the German working population collected in 2020 (N = 1986). Our results indicate that being more supportive of a UBI went along with being comparably younger, of East-German origin, and more in favor of equal living standards, as well as perceiving one's economic situation to be worse and the threat of the corona-pandemic to be higher. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
41. Unraveling the interplay of ferroptosis and immune dysregulation in diabetic kidney disease: a comprehensive molecular analysis.
- Author
-
Jiao, Yuanyuan, Liu, Xinze, Shi, Jingxuan, An, Jiaqi, Yu, Tianyu, Zou, Guming, Li, Wenge, and Zhuo, Li
- Subjects
DIABETIC nephropathies ,ARTIFICIAL neural networks ,TYPE 2 diabetes ,DIABETES complications ,WESTERN immunoblotting ,SUPPORT vector machines - Abstract
Background: Diabetic kidney disease (DKD) is a primary microvascular complication of diabetes with limited therapeutic effects. Delving into the pathogenic mechanisms of DKD and identifying new therapeutic targets is crucial. Emerging studies reveal the implication of ferroptosis and immune dysregulation in the pathogenesis of DKD, however, the precise relationship between them remains not fully elucidated. Investigating their interplay is pivotal to unraveling the pathogenesis of diabetic kidney disease, offering insights crucial for targeted interventions and improved patient outcomes. Methods: Integrated analysis, Consensus clustering, Machine learning including Generalized Linear Models (GLM), RandomForest (RF), Support Vector Machine (SVM) and Extreme Gradient Boosting (xGB), Artificial neural network (ANN) methods of DKD glomerular mRNA sequencing were performed to screen DKD-related ferroptosis genes.CIBERSORT, ESTIMATE and ssGSEA algorithm were used to assess the infiltration of immune cells between DKD and control groups and in two distinct ferroptosis phenotypes. The ferroptosis hub genes were verified in patients with DKD and in the db/db spontaneous type 2 diabetes mouse model via immunohistochemical and Western blotting analyses in mouse podocyte MPC5 and mesangial SV40-MES-13 cells under high-glucose (HG) conditions. Results: We obtained 16 differentially expressed ferroptosis related genes and patients with DKD were clustered into two subgroups by consensus clustering. Five ferroptosis genes (DUSP1,ZFP36,PDK4,CD44 and RGS4) were identified to construct a diagnostic model with a good diagnosis performance in external validation. Analysis of immune infiltration revealed immune heterogeneity between DKD patients and controls.Moreover, a notable differentiation in immune landscape, comprised of Immune cells, ESTIMATE Score, Immune Score and Stromal Score was observed between two FRG clusters. GSVA analysis indicated that autophagy, apoptosis and complement activation can participate in the regulation of ferroptosis phenotypes. Experiment results showed that ZFP36 was significantly overexpressed in both tissue and cells while CD44 was on the contrary.Meanwhile,spearman analysis showed both ZFP36 and CD44 has a strong correlation with different immune cells,especially macrophage. Conclusion: The regulation of the immune landscape in DKD is significantly influenced by the focal point on ferroptosis. Newly identified ferroptosis markers, CD44 and ZFP36, are poised to play essential roles through their interactions with macrophages, adding substantial value to this regulatory landscape. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
42. Relevance and Adoption of AI technologies in German SMEs – Results from Survey-Based Research.
- Author
-
Ulrich, Patrick and Frank, Vanessa
- Subjects
ARTIFICIAL intelligence ,GENERAL education ,MACHINE learning - Abstract
Artificial intelligence (AI) is regarded worldwide as one of the most important technologies of the future. In the international context, Germany is not considered a pioneer in the field of AI, and the implementation of AI technologies in German companies is also rather slow. Since the German economy is mainly driven by SMEs, the implementation of AI in SMEs is a key success factor of the national economy. It is known from general studies on digitalization that German SMEs are rather skeptical about new technologies. This paper discusses the implementation prospects of AI in German SMEs based on an empirical survey conducted in 2020 among 283 companies. It shows that the SMEs surveyed tend to use more traditional technologies such as rule-based systems and see the lack of employee qualifications in particular as an implementation hurdle. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
43. The Emergence and Rise of Industry 4.0 Viewed through the Lens of Management Fashion Theory.
- Author
-
Madsen, Dag Øivind
- Subjects
INDUSTRY 4.0 ,MANAGEMENT philosophy ,ECONOMIC elites ,ARTIFICIAL intelligence ,MANUFACTURING processes - Abstract
The Industry 4.0 (I4.0) concept is concerned with the fourth industrial revolution in manufacturing, in which technological trends such as digitalization, automation and artificial intelligence are transforming production processes. Since the concept's introduction at the Hannover Fair in Germany in 2011, I4.0 has enjoyed a meteoric rise in popularity and is currently high on the agenda of governments, politicians and business elites. In light of these observations, some commentators have asked the question of whether I4.0 is a concept that is hyped up and possibly just the latest in a long line of fashionable management concepts introduced over the course of the last few decades. Therefore, the aim of this paper is to provide a critical outside-in look at the emergence and rise of I4.0. Theoretically, these processes are viewed through the lens of management fashion, a theoretical perspective well suited to examinations of evolutionary trajectories of management concepts and ideas. The findings indicate that the I4.0 concept has quickly become highly popular and is dominating much of the popular management discourse. The concept has migrated out of the specialized manufacturing discourse to become a more general concept with mainstream appeal and applicability, evidenced by a multitude of neologisms such as Work 4.0 and Innovation 4.0. The numbers 4.0 have spread in a meme-like fashion, evidenced by the fact that the combination of a noun and the numbers 4.0 are used to signal and usher in discussions about the future of business and society. While there is much evidence that clearly shows that the concept has had a wide-ranging impact at the discursive level, the currently available research is less clear about what impact the concept has had so far on industries and organizations worldwide. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
44. Artificial intelligence in liver cancer research: a scientometrics analysis of trends and topics.
- Author
-
Rezaee-Zavareh, Mohammad Saeid, Kim, Naomy, Yee Hui Yeo, Hyunseok Kim, Jeong Min Lee, Sirlin, Claude B., Taouli, Bachir, Saouaf, Rola, Wachsman, Ashley M., Noureddin, Mazen, Zhiping Wang, Moore, Jason, Debiao Li, Singal, Amit G., and Ju Dong Yang
- Subjects
LIVER cancer ,ARTIFICIAL intelligence ,TREND analysis ,CANCER research ,SCIENTOMETRICS ,ADRENAL insufficiency - Abstract
Background and aims: With the rapid growth of artificial intelligence (AI) applications in various fields, understanding its impact on liver cancer research is paramount. This scientometrics project aims to investigate publication trends and topics in AI-related publications in liver cancer. Materials and Methods: We employed a search strategy to identify AI-related publications in liver cancer using Scopus database. We analyzed the number of publications, author affiliations, and journals that publish AI-related publications in liver cancer. Finally, the publications were grouped based on intended application. Results: We identified 3950 eligible publications (2695 articles, 366 reviews, and 889 other document types) from 1968 to August 3, 2023. There was a 12.7-fold increase in AI-related publications from 2013 to 2022. By comparison, the number of total publications on liver cancer increased by 1.7-fold. Our analysis revealed a significant shift in trends of AI-related publications on liver cancer in 2019. We also found a statistically significant consistent increase in numbers of AI-related publications over time (tau = 0.756, p < 0.0001). Eight (53%) of the top 15 journals with the most publications were radiology journals. The largest number of publications were from China (n=1156), the US (n=719), and Germany (n=236). The three most common publication categories were "medical image analysis for diagnosis" (37%), "diagnostic or prognostic biomarkers modeling & bioinformatics" (19%), and "genomic or molecular analysis" (18%). Conclusion: Our study reveals increasing interest in AI for liver cancer research, evidenced by a 12.7-fold growth in related publications over the past decade. A common application of AI is in medical imaging analysis for various purposes. China, the US, and Germany are leading contributors. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
45. Implementation of cloud computing in the German healthcare system.
- Author
-
Putzier, M., Khakzad, T., Dreischarf, M., Thun, S., Trautwein, F., and Taheri, N.
- Subjects
DIGITAL technology ,ARTIFICIAL intelligence ,MEDICAL care ,HUMAN services programs ,HEALTH care reform ,CLOUD computing ,DATA security ,HEALTH systems agencies - Abstract
With the advent of artificial intelligence and Big Data - projects, the necessity for a transition from analog medicine to modern-day solutions such as cloud computing becomes unavoidable. Even though this need is now common knowledge, the process is not always easy to start. Legislative changes, for example at the level of the European Union, are helping the respective healthcare systems to take the necessary steps. This article provides an overview of how a German university hospital is dealing with European data protection laws on the integration of cloud computing into everyday clinical practice. By describing our model approach, we aim to identify opportunities and possible pitfalls to sustainably influence digitization in Germany. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
46. The Management and the Advice of (Un)Explainable AI.
- Author
-
Dubovitskaya, Elena and Buchholz, Annika
- Subjects
FIDUCIARY responsibility ,ARTIFICIAL intelligence ,MACHINE learning ,ADVICE - Abstract
794 The article addresses the issue that is widely discussed in Germany and other jurisdictions: can the management of a company use AI applications in its decision-making process without violating its fiduciary duties? The lack of transparency in conventional AI applications conflicts with the fiduciary duty to check the plausibility of external expert advice (in Germany known as the ISION principles). This tension can be partly resolved by using explainable AI (XAI). In this work, we review the basic principles of machine learning and XAI and discuss them in the legal context. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
47. Al-based B-to-B brand redesign: A case study.
- Author
-
Albert, Vakhtang Daniel and Schmidt, Holger J.
- Subjects
ARTIFICIAL intelligence ,BUSINESS-to-business transactions ,INDUSTRY 4.0 ,BRANDING (Marketing) ,AWARENESS advertising ,BRAND name products - Abstract
Copyright of Transfer: Zeitschrift für Kommunikation & Markenmanagement is the property of Deutsche Werbewissenschaftliche Gesellschaft and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2023
48. Artificial Intelligence in studies—use of ChatGPT and AI-based tools among students in Germany.
- Author
-
von Garrel, Jörg and Mayer, Jana
- Subjects
ARTIFICIAL intelligence ,CHATGPT ,ENGINEERING students ,LANGUAGE models ,STUDENT surveys - Abstract
AI-based tools such as ChatGPT and GPT-4 are currently changing the university landscape and in many places, the consequences for future forms of teaching and examination are already being discussed. In order to create an empirical basis for this, a nationwide survey of students was carried out in order to analyse the use and possible characteristics of AI-based tools that are important to students. The aim of the quantitative study is to be able to draw conclusions about how students use such AI tools. A total of more than 6300 students across Germany took part in the anonymous survey. The results of this quantitative analysis make it clear that almost two-thirds of the students surveyed use or have used AI-based tools as part of their studies. In this context, almost half of the students explicitly mention ChatGPT or GPT-4 as a tool they use. Students of engineering sciences, mathematics and natural sciences use AI-based tools most frequently. A differentiated examination of the usage behaviour makes it clear that students use AI-based tools in a variety of ways. Clarifying questions of understanding and explaining subject-specific concepts are the most relevant reasons for use in this context. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
49. Your Boss Is an Algorithm: Artificial Intelligence, Platform Work and Labour.
- Author
-
BERNICCHIA-FREEMAN, ZOÉ
- Subjects
ARTIFICIAL intelligence ,ROBOTS ,AUTOMATION ,ALGORITHMS - Abstract
In March 1964, the cover page of a popular German weekly magazine entitled Der Spiegel painted a frightening picture: An anthropomorphic robot with six mechanical arms commands an assembly line while a displaced human worker floats aimlessly in the foreground. Ejected from his station, the worker throws up his hands in despair next to a headline that reads, "Automation in Germany, the arrival of robots." Over fifty years later, a cover page from the same magazine evoked similar themes: A giant robot arm yanks an office worker away from his computer under the headline, "You're fired! How computers and robots steal our jobs - and which jobs will be safe." The more things change, the more they stay the same. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
50. Simulation with a Lean Approach in Industry 5.0.
- Author
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Ramos Castillo, Mario, Perez Dominguez, Luis Asuncion, Romero López, Roberto, Sanchez-Mojica, Karla-Yoahana, and Burgos Pereira, Yunellis Del Carmen
- Subjects
ARTIFICIAL intelligence ,LEAN management ,MANUFACTURING processes ,INDUSTRY 4.0 ,INDUSTRIAL revolution ,DEVELOPING countries - Abstract
Lean Manufacturing is a methodology that companies from different sectors have implemented for several years, which has given significant results. Although it is a methodology that has been implemented since the 70's, it is still in force despite the technological era that has been advancing in recent years. The different Industrial Revolutions have brought with them important advances in terms of technology, always seeking to make life easier for human beings. From Industry 3.0, where we begin to talk about technology and intelligent machines, it has sought to automate processes and replace handmade or manual production in companies. Therefore, one might think that just as companies must adapt to these new trends, methodologies, such as Lean Manufacturing, should also transition to automation or the use of technology for their application. If Industry 3.0 already showed important signs in the advancement of technology, with Industry 4.0 it was confirmed that this technology would be present in our daily lives and in the processes of companies. In fact, in developed countries such as Japan and Germany there is already widespread talk of Industry 5.0, an industry that seeks to return to the human being as an important part of industrial processes, which in Industries 3.0 and 4.0 had passed into the background to give way and greater importance to the use of technology. With the new industrial revolution (5.0) there is even talk of new technologies and tools for improving the production processes of companies. Companies seeking to adapt to the use of technology and seek to continue competing in the market and even seek a better position against the competition must make strong capital investments to acquire the technology necessary for their processes. And those decision-makers need to have a very broad picture and make sure that those investments work and have the expected results. One of the important tools in Industry 5.0 that can help in decision making is simulation. The simulation helps in visualizing how a process works without the need for it to be already implemented in a real way, that is, adjustments and improvements can be made without these implying a change or an investment in the real process. Therefore, we can have data that approximates the data that can throw us a process that is already working physically. If you are looking to analyze data from a process that is already physically implemented, simulation helps determine which part of the process requires improvement or change. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
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